Case for omitting tied observations in the two-sample t-test and the Wilcoxon-Mann-Whitney Test.

ABSTRACT: When the distributional assumptions for a t-test are not met, the default position of many analysts is to resort to a rank-based test, such as the Wilcoxon-Mann-Whitney Test to compare the difference in means between two samples. The Wilcoxon-Mann-Whitney Test presents no danger of tied observations when the observations in the data are continuous. However, in practice, observations are discretized due various logical reasons, or the data are ordinal in nature. When ranks are tied, most textbooks recommend using mid-ranks to replace the tied ranks, a practice that affects the distribution of the Wilcoxon-Mann-Whitney Test under the null hypothesis. Other methods for breaking ties have also been proposed. In this study, we examine four tie-breaking methods-average-scores, mid-ranks, jitteri

SUBMITTER: McGee M 

PROVIDER: S-EPMC6057651 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature